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Advanced Python Programming for A-Level Students

Dive into advanced Python programming with topics like multi-dimensional arrays, dictionaries, exceptions, and more. Learn to represent data efficiently and handle complex programming tasks effectively.

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Advanced Python Programming for A-Level Students

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  1. TeachingLondon Computing A Level Computer ScienceTopic 3: Advanced Programming in Python William Marsh School of Electronic Engineering and Computer Science Queen Mary University of London

  2. Aims • Further topics in programming • Some Python-specific • Representing information • Arrays of multiple dimensions • Python built-in types: tuples, dictionaries; sequences • Exceptions: dealing with errors

  3. Two Representation Problems • Minesweeper squares • Flagged / tested / hidden • Mine / no mine • Number of neighbouring mines • Hangman words • Letter at each position • Letters used • Letters uncovered

  4. Hangman Example Complete word [ 'U', 'N', 'U', 'S', 'U', 'A', 'L'] Letters guessed [ 'A', 'E', 'T', 'S', 'R'] Current display [ '_', '_', '_', 'S', '_', 'A', '_'] Representation changes program

  5. Arrays of Multiple Dimensions Standard part of A Level

  6. Multidimensional Arrays X==0, Y==1 X==2, Y==3 Recall that Arrays are Lists in Python So far: arrays represent What about:

  7. Why Arrays? • An array is a sequence of memory locations • Simple and fundamental idea • Really, lists are represented using arrays • We use lists to learn about arrays

  8. Table of Data • Sum the columns in a table of data • Issues • Representation • Algorithm

  9. Table Representation table = [ \ [10, 27, 23, 32], \ [31, 44, 12, 65], \ [15, 17, 18, 23] \ [ 0, 0, 0, 0] \ ] • Table represented by list of lists • Quiz • table[0][1] == ? • table[1][2] == ?

  10. Printing a Column Use two indices def printCol1(table, colN): string = "" for rowN in range(0, len(table)): string += str(table[rowN][colN]) + " " print(string) Select List from Table defprintCol2(table, colN): string = "" for row in table: string += str(row[colN]) + " " print(string) Two methods

  11. Exercise: Sum Columns • Adapt the code on the previous slide to print the sum of: • A given column • Of all columns

  12. Built in Types in Python Important in Python programming Very useful Details specific to Python; related concepts elsewhere

  13. Overview • Lists – [1,2,3,4] • Ordered collection of items; often of the same type. • Can be changed (mutable) • Tuples – (1,2,3,4) • Immutable ordered collection; often different types • Ranges – range(1,5) • Number sequence; used in for loops • Sets – {1,2,3,4} • Unordered non-repeating collection • Dictionaries – {1:'one', 2:'two', 3:'three'} • Mappings

  14. Tuples – Examples defgetTwo(): ms = input("A string> ") nm = input("A number> ") return((ms, int(nm))) >>> getTwo() A string> Hello A number> 99 ('Hello', 99) >>> t = ("a", 1, [1]) >>> x,y,z = t >>> z [1] Assign to multiple variables Convenient for returning multiple values from a function Unpack

  15. Ranges – Examples for x in range(1,10,2): print("x =", x) x = 1 x = 3 x = 5 x = 7 x = 9 >> list(range(0,-10,-1)) [0, -1, -2, -3, -4, -5, -6, -7, -8, -9] In a for loop: Convert to a list

  16. Sequences Strings, lists, tuples and ranges are all sequences

  17. Mutable and Immutable • Mutable == can change • e.g. append an item to a list • Immutable == cannot change • Concatenating two lists does not change them • Copied when necessary • Lists, sets and dictionaries are mutable • Strings, tuples and ranges are immutable

  18. Sequences – Mutable Only

  19. Understanding Assignment x [1,2,3,4,5] y = x # assignment x [1,2,3,4,5] y Variables (and parameters) refer (or point) to objects Assignment (and function parameters) copy references

  20. Other Languages In Visual Basic, you can pass an argument to a procedure by value or by reference. This is known as the passing mechanism, and it determines whether the procedure can modify the programming element underlying the argument in the calling code. The procedure declaration determines the passing mechanism for each parameter by specifying the ByValor ByRefkeyword. Quoted from http://msdn.microsoft.com/en-gb/library/ddck1z30.aspx If an object is immutable, you cannot tell whether it is copied or referenced Issue: copying large objects (long arrays)

  21. Sets and Dictionaries • Set: a collection of unique objects • Not ordered • Mutable (but elements must be immutable) • Dictionary: a map from a key to a value • Unique key • Mutable (key must be immutable)

  22. Set Examples Making sets >>> s = {1,2,3} >>> t = set(range(2,11,2)) >>> t {8, 2, 10, 4, 6} >>> u = s.union([1,1,1]) >>> u {1, 2, 3} >>> u = s.intersection(t) >>> u {2} >>> len(s) 3 >>> {2,4}.issubset(t) True >>> s.issubset(t) False >>> Set operations

  23. Dictionary Examples Making a dictionary >>> d1 = {'milk':2,'eggs':6,'tea':1} >>> d1 {'eggs': 6, 'tea': 1, 'milk': 2} >>> len(d1) 3 >>> 'books' in d1.keys() False >>> 'records' in d1.keys() False >>> d2 = dict([((0,0),'B'),((0,1),'G'),((1,0),'B'),((1,1),'G')]) >>> d2 {(0, 1): 'G', (1, 0): 'B', (0, 0): 'B', (1, 1): 'G'} >>> d2[(1,1)] 'G' >>> d1['milk'] 2 Check keys Tuple as a key Dictionary look up

  24. Dictionaries versus Arrays In other languages, library has ‘dictionary’ data structure

  25. Exercise • Suggest two representations each for minesweeper and / or hangman • Write Python to create examples • Write Python to update the state • New location in the mine field tested • New letter guessed in hangman

  26. Exceptions What Happens When a Problem Occurs

  27. Exception – Example Traceback (most recent call last): File "<pyshell#32>", line 1, in <module> int("xyz") ValueError: invalid literal for int() with base 10: 'xyz' Error or “exception” name • int("XYZ") – leads to an error • Not a programming error: user input • Program stops:

  28. Exceptions – Trying it out • Try out the code • Certain errors possible • “Catch” the error (i.e. exception) if it occurs and • … run code to “handle” the error. • Words • “Exception” – a type of error, with a name • “Handle” – respond to the error nicely • “Catch” – jump to error-handling statement

  29. Exception – Syntax try: in_str = input("Enter a number> ") in_num = int(in_str) exceptValueError: print("Sorry", in_str, "is not an integer") Statements where exceptions may occur Two new keywords Only if exception occurs Example

  30. When to Use Exceptions • Robust code: check for errors • Why? • Either: Check error cannot occur • Or: Catch exceptions • Exceptions used: • User input • OS operation (opening a file) • When using library code

  31. Summary • Representing data • Aspect of problem solving • Easier in Python: build in ‘data structures’ • Handle exceptions for robust code

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